International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 06 | Jun 2024 www.irjet.net p-ISSN:2395-0072
ACCELERATING PROTOTYPE TO PRODUCTION APPLICATION DEVELOPMENT IN DATA ENGINEERING WITH SCALA
Sadha Shiva Reddy Chilukoori*1, Shashikanth Gangarapu*2, Chaitanya Kumar Kadiyala*3
Meta Platforms Inc., USA Qualcomm Inc., USA Arm Inc., USA ***
ABSTRACT:
This article looks at the benefits and drawbacks of using Scala, a modern multi-paradigm computer language, for quick prototypes in software development, mainly in the area of data engineering. We show through research, surveys, and case studiesthatScalaisagreatlanguageforquicklymakingprototypesbecauseithasasimplesyntax,astrongtypesystem,andit works well with many famous frameworks and libraries. Case studies show how well Scala works in real-lifesituations, like whenit'susedtomakeanORCinformationsearchappandanORCfiledefragmentationapp.TheresultsshowthatusingScala for quick prototyping is much more productive than using traditional programming languages like Java in terms of developmenttime,codequality,scalability,collaboration,feedbackloops,costsavings,andtotaloutput.
Keywords: Scala,QuickPrototyping,DataEngineering,PerformanceOptimization,SoftwareDevelopment
INTRODUCTION:
Quick prototyping is an important part of the software development lifecycle because it lets writers test and confirm ideas quickly.TheInternationalDataCorporation(IDC)polledpeopleand91%ofthemsaidthatquickprototypingisimportantfor makingsoftwareworkwell[1].WithmorepeoplewantingtouseagilesoftwaredevelopmentmethodslikeScrumandKanban,
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 06 | Jun 2024 www.irjet.net p-ISSN:2395-0072
workers need a language that can keep up with their work [2]. Modern multi-paradigm programming language Scala has a uniquesetoftraitsthatmakeitagreatchoiceformakingquickprototypes[3].
When compared to traditional languages like Java, Scala's short syntax lets writers say more with fewer lines of code. The UniversityofCalifornia,Berkeley,didastudythatshowedScalacodeisusually30–50%shorterthanJavacodethatdoesthe same thing [4]. Because it's short, developers can focus on the most important parts of their prototypes, which saves them timeandeffort.
Scala also has a strong type system and checks that happen at compile time that catch mistakes early in the development process.Thismakessurethatthecodeisgoodandeasytomanage[5].Twitterdidacasestudythatshowedthatswitchingto Scalacutthenumberofbugsinproductionby60%comparedtotheiroldJavaversion[6].
Scala also works well with well-known tools and libraries, like Apache Spark and Akka, so developers can make and use prototypes quickly that are scalable and efficient [7]. LinkedIn, a well-known Scala user, said that switching from Python to Scalacutthetimeittooktobuildtheirmachinelearningsystemsbyhalf[8].
We will look at two case studies that show how well Scala works for quick prototyping in data engineering in the next few parts.ThesecasestudiesshowhowScala'ssimplesyntax,strongtypesystem,andeasyintegrationwithbigdatatools makeit fastertomakeprototypesthatworkwellandcanbescaledup.
CASE STUDIES:
HerearetwocasestudiesshowcasingScala'seffectivenessforquickprototypingindataengineering: 1. ORC Metadata Search Application:
Inthiscasestudy,weusedScalatomakeanappthatsearchestheinformationofanORC(OptimizedRowColumnar)file.Itis common to store structured data in ORC files in the Hadoop environment. For example, Facebook says that their data
Fig.1:Scala'sAdvantagesOverJavainRapidApplicationDevelopment[1–8]
International
Volume: 11 Issue: 06 | Jun 2024 www.irjet.net p-ISSN:2395-0072
warehousehasover10petabytesofORCdata [9].TheappusesScala'sshortsyntaxandfunctional programmingfeaturesto quicklyreadandfindORCfilemetadata.
Theprototypewasmadeinjusttwodaysbyateamofthreeworkers,showingthatScalacancutdownondevelopmenttime. The program worked with an ORC file that was 10 gigabytes in size and had 100 million rows and 50 columns. The pattern matching and case classes in Scala made it easy for the developers to quickly get the information and change it. This meant thatsearchqueriesraninlessthan500milliseconds[10].
Scala'sability to handle parallel processing also let the app grow horizontally, spreading the metadata search across several nodesinaHadoopcluster.TheprogramcouldhandlebiggerORCfileswithoutslowingdownbecauseitwasscalable[11].
Table1:Scala-basedORCMetadataSearchApplicationPerformanceMetrics[9-11]
2. ORC FILE DEFRAGMENTATION APPLICATION:
In the second case study, an app is used to defragment ORC files that are used to store table data in Amazon S3. Faulty performanceandhigherstoragecosts canbecausedbydata fragmentation.Forexample,Amazonsays thatevery100MBof fragmenteddatacanaddonesecondtoquerydelay[12].
The Scala-based prototype uses the Apache Spark framework to organize ORC files quickly and effectively, which makes it easier to store and get data. In just one week, five workers worked together to make and test the prototype, which showed howwellScalaworkswithwell-knownbigdataframeworks.
Theappwastriedonadatasetwith1billionrowsspreadoutover1,000fragmentedORCfilesinAmazonS3.Thedatasetwas 1 terabyte in size. Scala's integration with Spark let the app use a cluster of 100 Amazon EC2 instances to handle the fragmentedfilesatthesametime[13].
TheprocessofdefragmentationcutthenumberofORCfilesby70%andthetotalsizeofthestorageby50%.Asaresult,query speedwentupby45%andstoragecostswentdownby40%[14]. Metric
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 06 | Jun 2024 www.irjet.net p-ISSN:2395-0072
Table2:ScalaandApacheSpark-basedORCFileDefragmentation:PerformanceandCostOptimization[12-14]
These case studies show how useful Scala is for quick prototyping in data engineering. They show how it can cut down on development time, handle large datasets quickly, and work with popular big data frameworks and cloud platforms without anyproblems.
KEY FINDINGS:
OurresultsdemonstratethatusingScalaforquickprototypingoffersseveralbenefits:
1. Faster Development Time:
Scala'sshortsyntaxandhigh-levelabstractionsletdevsfocusonthecorelogicofanappinsteadofwritingalotofcode.When compared to traditional computer languages, our case studies showed that prototypes were made in a lot less time. Scala needed30%fewerlinesofcodethanJavaonaveragetodothesamethings[15].
A study by the Scala Center at EPFL found that developers who used Scala cut the time it took to work on projects by 22% compared to developers who used other languages [16]. For example, three developers made the prototype of the ORC metadata search application in just two days, which is 40% less time than they thought it would take to make the app using Java.
2. Improved Code Quality:
Scala'sstrongtypesystemandchecksthathappenatcompiletimemakesurethatcodeiscorrectandeasytomanage,which lowers the chance of bugs and errors. Scala's type inference and pattern-matching tools helped us find possible problems earlierinthedevelopmentprocess.Thisledtobettercodequalityandfewererrorsatruntime[17].
Itwasfoundby Artima Inc. thatScala projectshad40% fewerbugsperlineofcode thanJava projectsofthesamesize[18]. Scala'stypesystemcaught15possibleruntimeerrorsintheORCfiledefragmentationapplicationwhileitwasbeingcompiled. Thiskeptthemistakesfromhappeninginproduction.
3. Easier Scalability:
Scala works well with well-known tools and libraries like Apache Spark and Akka, which makes it simple to create and use prototypes that are scalable and efficient [19]. Scala's ability to work with Spark made it possible to process big amounts of dataquicklyintheORCfiledefragmentationcasestudy,showingitsscalabilitybenefits.
Acollectionof100AmazonEC2instanceswereusedtoprocess1terabyteofdataspreadacross1,000fragmentedORCfiles. Scala's integration with Spark made it possible for the app to handle the data in just two hours, which is 60% faster than a similarHadoop-basedimplementation[20].
4. Better Collaboration:
Scala's short syntax and expressive nature make it easier for devs working on prototypes to talk to each other and work together [21]. In our case studies, it was easier for team members to understand and add to each other's code, which made themworktogetherbetterandgetmoredone.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 06 | Jun 2024 www.irjet.net p-ISSN:2395-0072
A case study by Swiss Re found that when teams adopted Scala, they worked together 30% more because the language's readabilityandexpressivenessmadeiteasierforcoderstoshareandtalkaboutcode[22].
5. Faster Feedback:
Scala's fast compilation and runtime let writers get feedback on their prototypes quickly, which speeds up the process of iterating and improving [23]. Developers could quicklytry and improve the search functionality in the ORC metadata search app,whichspedupthefeedbackloop.
The application's test suite, which covered 95% of the codebase, was run in less than two minutes, giving devs almost immediatefeedbackonhowwellandhowwelltheprototypeworked[24].
6. Reduced Costs:
Scala'sspeedand ability to grow help lower the costs ofdeveloping, deploying,and maintaining software[25]. Scala'sspeed improvementsandabilitytoconnecttocheapcloudstorageserviceslikeAmazonS3savedalotofmoneycomparedtoother methodsusedintheORCfiledefragmentationcasestudy.
For the company, the defragmentation process cut storage prices by half, which saved them $50,000 a month [26]. Additionally, better query speed meant that more computing resources were not needed, which cut infrastructure costs by 30%.
7. Increased Productivity:
Scala's clear syntax and high-level abstractions let devs focus on the most important parts of their app, which speeds up development and makes them more productive [27]. In our case studies, developers said they were 25% more productive whentheyusedScalafortestingthanwhentheyusedotherlanguages.
TheScalaCenterdida poll andfoundthatdeveloperswhousedScalawere20%moreproductivethandeveloperswhoused other languages [28]. Scala's short and clear syntax let developers add complex features with fewer lines of code, which cut downonthetimeneededtowriteandmanagethecodebase.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 06 | Jun 2024 www.irjet.net p-ISSN:2395-0072
CONCLUSION
:
The evidence presented in this study strongly suggests that Scala should be used for rapid prototyping in software development,especiallyindataengineering.Combiningresearch,surveys,andreal-lifecasestudiesshowsthatScala'sunique qualities,includingshortsyntax,astrongtypesystem,andeasyintegrationwithfamousframeworks,makeitagreat language forquicklymakingprototypes.
The case studies show how Scala can shorten the time it takes to create software, make it more scalable, help people work together better, give faster feedback, cut costs, and boost overall productivity. These benefits are very important in today's fast-pacedsoftwaredevelopmentworld,wherequickprototypingisneededtotestideasandgetgoodstomarketquickly.
Inaddition,theresultsshowthatusingScalaforquickprototypescanmakemanypartsofthesoftwaredevelopmentlifecycle muchbetter.Scalahastheabilitytochangethewaysoftwareprototypesaremadebecauseitcutsdownondevelopmenttime, bugs,andcostswhilealsomakingpeoplemoreproductiveandabletoworktogether.
Scala is becoming more and more famous as a language for making quick prototypes as the need for agile software developmentgrows.Scalaisakeyplayerinthefutureofsoftwaredevelopmentbecauseitcansolvetheproblemsthatcoders faceinfieldsthatchangequickly,likedataengineering.
Intheend,thedatainthispaperstronglysuggeststhatScalashouldbeusedforquickprototypinginsoftwaredevelopment. It's a great tool for developers who want to speed up the testing process and make high-quality, scalable apps in less time becauseithasauniquesetoffeaturesthathavebeenshowntoworkintherealworld.
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